Biomedical signals from many sources including heart, brain and endocrine system pose a challenge to researchers who may have to separate weak signals arriving from multiple sources contaminated with artifacts and noise. The analysis of these signals is important both for research and for medical diagnosis and treatment. The main difficulty in dealing with biomedical signals is the extreme vari...

Independent component analysis (ICA) is increasing in popularity in the field of biomedical signal processing. It is generally used when it is required to separate measured multi-channel biomedical signals into their constituent underlying components. The use of ICA has been facilitated in part by the free availability of toolboxes that implement popular flavours of the techniques. Fundamentall...

Blind Source Separation (BSS) is a prominent problem in signal processing. In the past few decades, it was applied to many fields, in which separation of compound signals, simultaneously observed by different sensors, is of interest. The problem can be considered as built-up of three physical elements: sources (also called transmitters), sensors (also called receivers) and communication channel...

(1) Computational Neurobiology Laboratory, Howard Hughes Medical Institute The Salk Institute for Biological Studies; (2) Institute for Neural Computation, University of California San Diego, La Jolla CA; (3) Department of Biology, University of California San Diego, La Jolla CA. (4) Naval Health Research Center, San Diego CA; (5) Department of Medicine (Neurology), Duke University (6) Brain Im...

In the present paper we shall examine the real-time restoration of biomedical signals under additive noises. Biomedical signals measured by instruments such as catheter manometers, ambulatory electrocardiographs and thermo-dilution sensors are susceptible to distortion and noise. Therefore, such signals must be restored to their original states. In the present study, nonstationary biomedical si...

In this work, a novel ECG data compression method is presented which employs set partitioning in hierarchical trees algorithm(SPIHT) on two dimensional electrocardiogram(2D-ECG).The 2D ECG is a two dimensioned array, in which each row of this array indicates one or more period and amplitude[7] normalized ECG beats. When SPIHT algorithm is used to compress one or two-dimensional signals separate...

We describe a generalization of traditional coherence that estimates the relationship between frequency components of one or two signals at different frequencies. The key idea of this technique is to apply amplitude modulation to one of the signals prior to a traditional coherence analysis. The modulated coherence includes traditional coherence as a special case. This is useful for identifying ...

Electrocardiogram (ECG) and magnetocardiogram (MCG) signals are among the most considerable sources of noise for other biomedical signals. In some recent works, a Bayesian filtering framework has been proposed for denoising the ECG signals. In this paper, it is shown that this framework may be effectively used for removing cardiac contaminants such as the ECG, MCG and ballistocardiographic arti...